Evidence map›Paper›PMID 37126158›Full record

ReviewJournal of mammary gland biology and neoplasia2023

Culture Models to Investigate Mechanisms of Milk Production and Blood-Milk Barrier in Mammary Epithelial Cells: a Review and a Protocol.

Ken Kobayashi

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of mammary gland biology and neoplasia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
15.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 44 citations in OpenAlex.

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  10. Differential expression ofVeterinary world · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Ken KobayashiLaboratory of Cell and Tissue Biology, Research Faculty of Agriculture, Hokkaido University, North 9, West 9, Sapporo, 060-8589, Japan. kkobaya@agr.hokudai.ac.jp.
Hokkaido University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mammary epithelial cells (MECs) are the only cell type that produces milk during lactation. MECs also form less-permeable tight junctions (TJs) to prevent the leakage of milk and blood components through the paracellular pathway (blood-milk barrier). Multiple factors that include hormones, cytokines, nutrition, and temperature regulate milk production and TJ formation in MECs. Multiple intracellular signaling pathways that positively and negatively regulate milk production and TJ formation have been reported. However, their regulatory mechanisms have not been fully elucidated. In addition, unidentified components that regulate milk production in MECs likely exist in foods, for example plants. Culture models of functional MECs that recapitulate milk production and TJs are useful tools for their study. Such models enable the elimination of indirect effects via cells other than MECs and allows for more detailed experimental conditions. However, culture models of MECs with inappropriate functionality may result in unphysiological reactions that never occur in lactating mammary glands in vivo. Here, I briefly review the physiological functions of alveolar MECs during lactation in vivo and culture models of MECs that feature milk production and less-permeable TJs, together with a protocol for establishment of MEC culture with functional TJ barrier and milk production capability using cell culture inserts.

Indexed as

LactationMilkAnimalsEpithelial CellsFemaleMammary Glands, AnimalSignal TransductionCulture modelMammary epithelial cellMembrane proteinsMilk productionTight junction

Identifiers

PMID37126158
PMCPMC10151314
OpenAlexW4367601073

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.